OPAH a model for optimal design of multipurpose small hydropower plants

The investment in small hydropower plants requires the analysis of hydrological, technical, operational, budgetary, economical and financial aspects. The analysis of each possible configuration demands the joint action of several technicians, consuming substantial time and money. During initial design of the project, simplified procedures are usually adopted which may compromise the quality of the base configuration.In this paper we will present a global overview of the OPAH model, which was developed to surpass these limitations. This global model performs the optimization of project configuration. This model uses non-linear programming optimization to analyze the multipurpose operation of the hydropower plant. It uses a numeric simulation model of unsteady flow under pressure to analyze the hydraulic circuit. It uses an economical and financial simulation model that takes in to account the project risk associated to hydrologic and market variability, the financial capacity of the investor and the fiscal aspects.     

Synthesis and properties of cinnamic acid series organic UV ray absorbents–interleaved layered double hydroxides

Organic ultraviolet (UV) ray absorbents, cinnamic acid (CA) and p-methoxycinnamic acid (PMOCA) were intercalated into Zn₂Al layered double hydroxides (Zn₂Al-LDHs) by co-precipitation reaction. The organic–inorganic nanocomposites, Zn₂Al-LDH/CA and Zn₂Al-LDH/PMOCA were obtained. The samples showed excellent UV ray absorption ability and their catalytic activity for the air oxidation of castor oil greatly decreased when the organic UV ray absorbents were intercalated in the layers of the Zn₂Al-LDHs. The studies suggested that Zn₂Al-LDH/organic UV absorbent nanocomposites might be used as safe sunscreen materials.     

Use of perlite as a pozzolanic addition in producing blended cements

There are ∼6700 million tons of perlite reserves in the world and two thirds of this amount takes place in Turkey. Although perlite possesses pozzolanic properties, it has not been so far used in producing blended cements. This study focuses on the use of natural perlites in blended cement production. For this purpose, after examining the suitability of the perlites as pozzolans and their ease of grindability, 16 types of blended cements having 320 m²/kg or 370 m²/kg Blaine fineness were produced by using 20% or 30% perlite additions. Production of the blended cements were accomplished either by intergrinding or separate grinding. The performance of the cements was evaluated by conducting the following tests: particle size distribution by laser diffraction, normal consistency, setting time, soundness and compressive strength. The results showed that perlites possess sufficient pozzolanic characteristics to be used in production of blended cement.     

Groundwater-surface water interactions and agricultural nutrient transport in a Great Lakes clay plain system

Nutrient export from agricultural land to surface waters is a significant environmental concern within the Great Lakes Basin (GLB). A field-based watershed-scale study was completed to investigate spatial and temporal variations of phosphorus and nitrate to assess nutrient transport pathways and groundwater-surface water interactions in an agriculturally dominated clay plain system. This was conducted in the 127 km² Upper Parkhill Watershed, near Lake Huron in southwestern Ontario, Canada. Data collection occurred from June 2018 to May 2019 via continuous sensor deployment and discrete sampling of stream water, groundwater, hyporheic zone, and tile drainage water. Samples were analyzed for various nutrient species (total, total dissolved, soluble reactive, and particulate phosphorus, and nitrate-N) to examine the hydrological dynamics of principal transport pathways of agriculturally-derived nutrients. Total phosphorus and nitrate concentrations in stream water ranged from 0.007 to 0.324 mg/L and 0.32 to 13.13 mg NO₃^?-N/L, respectively. Tile drainage water total phosphorous concentrations varied from 0.006 to 0.066 mg/L. Groundwater total dissolved phosphorus concentrations ranged from <0.003 to 0.085 mg/L. Transport of phosphorus through tile drainage was observed to be greater than through groundwater over the study period. No distinct relationship was observed between nutrient concentrations in the hyporheic zone and the vertical hydraulic gradient within this zone in the studied stream reach. Preliminary correlations were discerned between water quality observations and recognized land management practices. Given the elevated stream nutrient concentrations, these results are consequential for the continual improvement of strategies and programs devised to conserve water resources within the GLB.     

基于极限学习机的堤防工程多元风险指标评价方法

为提高堤防工程风险评价的准确性,提出了基于极限学习机的堤防工程多元风险指标评价方法。首先,综合考虑影响堤防风险的28个评价指标,利用层次分析法从预警系统、堤防工程系统、环境系统和社会经济系统这4个方面建立了堤防工程多元风险评价指标体系。接着,基于极限学习机算法对28个指标进行标准化处理及分级标准构建,以风险指标作为输入量,分级隶属度作为输出量,划分风险等级,量化评价指标,估计多元风险评价指标值和判断风险的严重程度。最后,依托鄱阳湖重点堤防——康山大堤,构建多元风险评价指标体系,运用极限学习机算法计算多元风险评价指标值。评价结果表明:康山大堤目前处于基本安全水平,符合康山大堤经过两次加固后的工程实际情况,并与其他方法进行对比,验证了提出方法的可靠性和有效性。该方法可拓展应用到其他重要水工结构工程风险评估中。     

Short-term load forecasting using bayesian neural networks learned by Hybrid Monte Carlo algorithm

This paper presents a short term load forecasting model based on Bayesian neural network (shorted as BNN) learned by the Hybrid Monte Carlo (shorted as HMC) algorithm. The weight vector parameter of the Bayesian neural network is a multi-dimensional random variable. In learning process, the Bayesian neural network is considered as a special Hamiltonian dynamical system, and the weights vector as the system position variable. The HMC algorithm is used to learn the weight vector parameter with respect to Normal prior distribution and Cauchy prior distribution, respectively. The Bayesian neural networks learned by Laplace algorithm and HMC algorithm and the artificial neural network (ANN) learned by the BP algorithm were used to forecast the hourly load of 25 days of April (Spring), August (Summer), October (Autumn) and January (Winter), respectively. The roots mean squared error (RMSE) and the mean absolute percent errors (MAPE) were used to measured the forecasting performance. The experimental result shows that the BNNs learned by HMC algorithm have far better performance than the BNN learned by Laplace algorithm and the neural network learned BP algorithm and the BNN learned by HMC has powerful generalizing capability, it can welly solve the overfitting problem.     

A GRASP × ELS approach for the job-shop with a web service paradigm packaging

The Job-Shop Scheduling Problem (JSSP) is well known for its complexity as an NP-hard disjunctive scheduling problem. The problem addressed in this paper is JSSPs with an objective of minimizing makespan while satisfying a number of hard constraints. An efficient GRASP × ELS approach is introduced for solving this problem. The efficiency is evaluated using the widely known 40 Laurence’s instances which encompass medium and large scale instances. The computational results prove that the proposed method competes with the best published methods in both quality of results and computational time. Recently, Web services have generated great interest in researchers. Such application architecture is based on the client–server model using existing Internet protocols and open standards. It provides new approaches to optimization methods. The proposed GRASP × ELS is packaged into a Web Service (WS), i.e., it offers for the research community an open access to our optimization approach. Moreover, the proposed web service can be even included in research future works with a very small programming effort.To favor utilization of the web service and to prove the facility in which the service could be used, we provide an example in Java proving that it is possible to obtain in less than 10 min a client application using the different methods exposed by this web service. Such usage extends to classical library inclusion in program with the difference that a method is called in the client side and represents an execution on the server.The Web Service paradigm is a new approach in spreading algorithms and therefore this paper stands at the crossroads of optimization research community and the web service community expectations. The GRASP × ELS provided in the web service, is a state of the art method which competes with previously published ones and which has the advantage of being available for free, in any languages, everywhere contributing in spreading operational research contribution.     

A 5 GHz LC-VCO frequency synthesizer for unlicensed band of WiMAX

This paper presents a low power and low phase noise CMOS integer-N frequency synthesizer based on the charge-pump Phase Locked Loop (PLL) topology. The frequency synthesizer can be used for IEEE 802.16 unlicensed band of WiMAX (World Interoperability for Microwave Access). The operation frequency of the proposed design is ranged from 5.13 to 5.22 GHz. The proposed Voltage-Controlled Oscillator (VCO) achieves low power consumption and low phase noise. The high speed divider is implemented by an optimal extended true single phase clock (E-TSPC) prescaler. It can achieve higher operating frequency and lower power consumption. A new frequency divider is also proposed to eliminate the hardware overhead of the S counter in the conventional programmable divider. The proposed frequency synthesizer consists of a phase-frequency detector (PFD), a charge pump, a low-pass loop filter, a VCO, and a frequency divider. The simulated phase noise of the proposed VCO is −121.6 dBc/Hz at 1 MHz offset from the carrier frequency. The proposed frequency synthesizer consumes 13.1 mW. The chip with an area of 1.048 × 1.076 mm² is fabricated in a TSMC 0.18 μm CMOS 1P6M technology process.     

Robust spatial flood vulnerability assessment for Han River using fuzzy TOPSIS with α-cut level set

This study aims to improve the general flood vulnerability approach using fuzzy TOPSIS based on α-cut level sets which can reduce the uncertainty inherent in even fuzzy multi-criteria decision making process. Since fuzzy TOPSIS leads to a crisp closeness for each alternative, it is frequently argued that fuzzy weights and fuzzy ratings should be in fuzzy relative closeness. Therefore, this study used a modified α-cut level set based fuzzy TOPSIS to develop a spatial flood vulnerability approach for Han River in Korea, considering various uncertainties in weights derivation and crisp data aggregation. Two results from fuzzy TOPSIS and modified fuzzy TOPSIS were compared. Some regions which showed no or small ranking changes have their centro-symmetric distributions, while other regions whose rankings varied dynamically, have biased (anti-symmetric) distributions. It can be concluded that α-cut level set based fuzzy TOPSIS produce more robust prioritization since more uncertainties can be considered. This method can be applied to robust spatial vulnerability or decision making in water resources management.